In agriculture, sustainability is framed as an aspiration to achieve multiple goals including positive production, environmental and social outcomes. These aspirations include: increasing production of nutritious food; minimising risk and maximising resilience in response to climate variability, fluctuating markets and extreme weather events; minimising impacts on global warming by reducing emissions; efficiently using limited resources; minimising negative on-site and off-site impacts; preserving biodiversity on farm and in nature; and achieving positive social outcomes reflected in farmers’ incomes (revenue and profit). Here we used cropping systems simulation to assess multiple (11) sustainability indicators for 26 crop rotations to quantify their sustainability throughout Australia’s subtropical cropping zone. Results were first expressed via a series of maps quantifying the minimal environmental impacts of attributes such as N applied, N leached, runoff and GHG emissions of the 26 crop rotations while identifying the locations of the optimal rotation for each attribute. Inspection of these maps showed that different rotations were optimal, depending on both location and the attribute mapped. This observation demonstrated that an 11-way sustainability win-win across all attributes was not likely to happen anywhere in the cropping zone. However, rotations that minimised environmental impacts were often among the more profitable rotations. A more holistic visualisation of the sustainability of six contrasting sites, using sustainability polygons, confirmed that trade-offs between sustainability indicators are required and highlighted that cropping in different sites is inherently more or less sustainable, regardless of the rotations used. Given that trade-offs between the various sustainability attributes of crop rotations are unavoidable, we plotted trade-off charts to identify which rotations offer an efficient trade-off between profit and other sustainability indicators. We propose that these maps, sustainability polygons and trade-off charts can serve as boundary objects for discussions between stakeholders interested in achieving the sustainable intensification of cropping systems.

在农业中，可持续性被定义为实现多个目标的愿望，包括积极的生产、环境和社会成果。这些愿望包括： 增加营养食品的生产；最大限度地减少风险并最大限度地提高应对气候变化、波动的市场和极端天气事件的复原力；通过减少排放最大限度地减少对全球变暖的影响；有效利用有限资源；尽量减少现场和场外的负面影响；保护农场和自然界的生物多样性；并实现反映在农民收入（收入和利润）上的积极社会成果。在这里，我们使用种植系统模拟来评估 26 次轮作的多个 (11) 可持续性指标，以量化其在整个澳大利亚亚热带种植区的可持续性。结果首先通过一系列地图来表示，这些地图量化了 26 次轮作的施氮、氮浸出、径流和温室气体排放等属性的最小环境影响，同时确定了每个属性的最佳轮作位置。对这些地图的检查表明，不同的旋转是最佳的，这取决于位置和映射的属性。这一观察结果表明，跨所有属性的 11 向可持续性双赢不太可能发生在种植区的任何地方。然而，最小化环境影响的轮换往往是利润更高的轮换之一。使用可持续性多边形对六个对比站点的可持续性进行更全面的可视化，确认需要在可持续性指标之间进行权衡，并强调无论使用何种轮作，不同地点的种植本质上或多或少都是可持续的。鉴于作物轮作的各种可持续性属性之间的权衡是不可避免的，我们绘制了权衡图表来确定哪些轮作在利润和其他可持续性指标之间提供了有效的权衡。我们建议这些地图、可持续性多边形和权衡图可以作为对实现种植系统可持续集约化感兴趣的利益相关者之间讨论的边界对象。我们绘制了权衡图表来确定哪些轮换提供了利润和其他可持续性指标之间的有效权衡。我们建议这些地图、可持续性多边形和权衡图可以作为对实现种植系统可持续集约化感兴趣的利益相关者之间讨论的边界对象。我们绘制了权衡图表来确定哪些轮换提供了利润和其他可持续性指标之间的有效权衡。我们建议这些地图、可持续性多边形和权衡图可以作为对实现种植系统可持续集约化感兴趣的利益相关者之间讨论的边界对象。